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This systematic literature review addresses the friction between deploying AI in critical infrastructure like healthcare and defense and navigating fragmented regulatory landscapes. It identifies specific hurdles such as compliance burdens on SMEs and misaligned governance models while proposing practical solutions like risk-tiered regulation and explainable AI to harmonize oversight with innovation. The findings offer a clear roadmap for policymakers and practitioners aiming to scale trustworthy AI without stifling technological progress in sensitive sectors.
Surse care acoperăarXiv, 36Kr, MIT News, SiliconANGLE

The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2606.12423v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) into critical infrastructure including healthcare, finance, energy, and defense, offers transformative benefits but also conflicts with evolving regulatory and governance frameworks. This paper presents a systematic literature review (SLR) to examine the challenges of balancing AI compliance and technological innovation across critical infrastructure sectors. The review follows established SLR guidelines to extract and synthesize insights from peer-reviewed articles, report, and institutional sources published between 2020-2025. The study identifies three interrelated challenges: fragmented regulations, excessive compliance burdens for smaller to medium enterprises (SMEs), and misaligned governance models. To address these challenges, the study highlights practical governance strategies, including risk-tiered regulation, compliance by design, and explainable AI, to support scalable and trustworthy AI deployment in critical sectors. Key contributions include a concise mapping of core AI-governance challenges and a conceptual diagram illustrating their overlap, as well as actionable strategies for policymakers and practitioner to harmonize oversight with innovation.

Abstract:The rapid integration of artificial intelligence (AI) into critical infrastructure including healthcare, finance, energy, and defense, offers transformative benefits but also conflicts with evolving regulatory and governance frameworks. This paper presents a systematic literature review (SLR) to examine the challenges of balancing AI compliance and technological innovation across critical infrastructure sectors. The review follows established SLR guidelines to extract and synthesize insights from peer-reviewed articles, report, and institutional sources published between 2020-2025. The study identifies three interrelated challenges: fragmented regulations, excessive compliance burdens for smaller to medium enterprises (SMEs), and misaligned governance models. To address these challenges, the study highlights practical governance strategies, including risk-tiered regulation, compliance by design, and explainable AI, to support scalable and trustworthy AI deployment in critical sectors. Key contributions include a concise mapping of core AI-governance challenges and a conceptual diagram illustrating their overlap, as well as actionable strategies for policymakers and practitioner to harmonize oversight with innovation.

Computers and Society (cs.CY); Artificial Intelligence (cs.AI)

arXiv:2606.12423 [cs.CY]

(or arXiv:2606.12423v1 [cs.CY] for this version)

https://doi.org/10.48550/arXiv.2606.12423 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.24251/HICSS.2026.540 Focus to learn more DOI(s) linking to related resources

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